The present disclosure generally relates to enabling computer vision, and more specifically, improving efficiency for detecting features using computer vision.
Computer vision is a field that includes methods for acquiring, processing, analyzing, and understanding images for use in applications. Traditionally, a processor, coupled to a sensor, acquires image data from a sensor and performs certain computer vision (CV) operations on the information received from the sensor for detecting CV features and consequently objects associated with those features. CV features may include features such as edges, corners, etc. These features may be used in determining macro features, such as faces, smiles and gestures. Programs executing on the processor may utilize the detected features in a variety of applications, such as plane-detection, face-detection, smile detection, gesture detection, etc.
Much effort has been made in recent years to enable computing devices to detect features and objects in the field of view of the computing device. Computing devices, such as mobile devices, are designed with sensitivity towards the amount of processing resources and power used by the mobile device and heat dissipation. However, traditionally, detecting features and objects in the field of view of the computing device, using a camera, requires significant processing resources resulting in higher power consumption and lower battery life in computing devices, such as mobile devices.